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Financial crisis, Value-at-Risk forecasts and the puzzle of dependency modeling
Berger, Theo; Missong, Martin - In: International review of financial analysis 33 (2014), pp. 33-38
Persistent link: https://www.econbiz.de/10010520086
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Value at risk estimation for heavy tailed distributions
Gammoudi, Imed; BelKacem, Lotfi; El Ghourabi, Mohamed - In: The international journal of business and finance … 8 (2014) 3, pp. 109-125
Persistent link: https://www.econbiz.de/10010241908
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Factor high-frequency based volatility (HEAVY) models
Sheppard, Kevin; Xu, Wen - 2014
Persistent link: https://www.econbiz.de/10010365630
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Volatility timing : how best to forecast portfolio exposures
Clements, A.; Silvennoinen, A. - In: Journal of empirical finance 24 (2013), pp. 108-115
Persistent link: https://www.econbiz.de/10010371987
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Measuring risk in fixed income portfolios using yield curve models
Caldeira, João F.; Moura, Guilherme Valle; Santos, … - In: Computational economics 46 (2015) 1, pp. 65-82
Persistent link: https://www.econbiz.de/10011441011
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The economic value of volatility timing with realized jumps
Nolte, Ingmar; Xu, Qi - In: Journal of empirical finance 34 (2015), pp. 45-59
Persistent link: https://www.econbiz.de/10011556992
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Value at Risk (VaR) models : a comparative analysis of parametric and non parametric approaches
Ajassa, Giovanni (contributor);  … - 1998
Persistent link: https://www.econbiz.de/10001435254
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Multivariate Nonparametric Estimation of Value at Risk and Expected Shortfall for Nonlinear Returns Using Extreme Value Theory
Brauchler, Ryan - 2012
estimators of market risk. Despite advances in the theory and practice of evaluating risk, existing measures are notoriously poor … extreme value theory (EVT) to propose a multivariate estimation procedure for value-at-risk (VaR) and expected shortfall (ES …
Persistent link: https://www.econbiz.de/10013100621
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Value-at-Risk Forecasting Ability of Filtered Historical Simulation for Non-Normal GARCH Returns
Adcock, Christopher J. - 2013
Persistent link: https://www.econbiz.de/10013090404